Hello everyone,

I have a data frame (tt), see below (I only show 2 genes, actually I have a
lot):

  group                    gene1       gene2  Control 28.9776 9.9355
Control 28.9499 10.0997  Control 29.5468 14.2995  Control 29.5246 13.9561
Test1 29.1864 9.7718  Test1 29.2048 10.0388  Test1 34.9563 11.9509  Test1
34.9464 11.8909  Test2 36.9566 14.5316  Test2 37.1309 14.5188  Test2 36.1017
29.5468  Test2 36.0883 29.5246
I'd like to calculate p values: Test1 vs Control and  Test2 vs Control
respectively for Gene1. Similar calculate performed for Gene2.

I tried:

sapply(levels(fac), function(x) t.test(tt1$gene1,
tt$gene1[which(fac==x)])$p.value)  # I don't really understand how it
works, I copied from genefilter.

where: fac=as.factor(tt$group)

It seemed to work for first column.  I don't know how to use apply() to
make it work on rest of column because I used tt$gene1 specifically. Or
whatever method that works

Thank you in advance.

Junyu

        [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to